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首页> 外文期刊>Atmospheric environment >A very-high resolution (20m) measurement-based dust emissions and dispersion modeling approach for the Oceano Dunes, California
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A very-high resolution (20m) measurement-based dust emissions and dispersion modeling approach for the Oceano Dunes, California

机译：基于高分辨率（20m）基于测量的粉尘排放和弥散建模方法，用于加利福尼亚的Oceano Dunes

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This study shows the results from very high-resolution (20 m) dust emissions and transport simulations for the Oceano Dunes State Vehicular Recreation Area (ODSVRA), a coastal sand dune complex located in San Luis Obispo County, California. Field data from an enhanced observation period carried out in May-July 2013 helped estimate the emissions and flow conditions over the dune field. Emissions are based on a comprehensive emissions grid developed from in-situ measurements using the Portable In-Situ Wind ERosion Lab (PI-SWERL). PI-SWERL estimates the potential for a soil surface to produce PM ic , dust emissions for a range of wind speeds. This approach provided a well-determined PM10 emissions field as a function of time and space. Wind and turbulence fields were estimated using the CALMET diagnostic meteorological model constrained with surface stations, upper air soundings, buoys, and the North American Reanalysis data. Hourly, three-dimensional wind flow and instability objective analysis fields were developed at 20 m resolution in order to consider the complex flow over realistic dune morphology, land use/land cover and terrain characteristics over and around the Oceano Dunes. The dust dispersion simulations were performed using a computationally efficient and vectorized Lagrangian Stochastic Particle Dispersion Model driven by the CALMET output and the PI-SWERL time-space variable emissions. The dispersion model is based on the Langevin formulation and includes the turbulent diffusion and stochastic particle motion (of millions of particles) in the inertial sub-range, and assuming particles as discrete units neglecting deposition. The model estimates diffusion of particles from an initial particle releases that scale according to the PI-SWERL time-variable emissions estimates. Results were then tested at two independent-downwind locations, with positive correlations for flow conditions (R-2 = 0.89) and similar receptor PM10 concentrations (R-2 = 0.85). Evaluations against those observations during mean flow conditions as well as for elevated dust events suggest that the model framework can capture the spatial and temporal characteristics of mean day-to-day and diurnal PM10 variability. In this study we describe the details of the model framework and its performance as well as its implementation to locate the dust sources that have the strongest impact in the receptor sites and to evaluate the impact of different dust reduction strategies used at the ODSVRA to mitigate PM10 at downwind receptors.
机译：这项研究显示了位于加利福尼亚州圣路易斯奥比斯波县的沿海沙丘大洋洲沙丘州汽车休闲区（ODSVRA）的超高分辨率（20 m）尘埃排放和运输模拟结果。 2013年5月至7月进行的观测期延长后的现场数据有助于估算沙丘场的排放和流动状况。排放基于使用便携式现场风蚀实验室（PI-SWERL）进行现场测量而开发的综合排放网格。 PI-SWERL估算了在一定风速下土壤表面产生PM ic，粉尘排放的可能性。这种方法根据时间和空间提供了确定的PM10排放场。风和湍流场是使用CALMET诊断气象模型估算的，该模型受地面站，高空探测，浮标和北美再分析数据的约束。每小时以20 m分辨率开发三维风流和不稳定性客观分析场，以考虑大洋沙丘及其周围沙丘形态，土地利用/土地覆盖和地形特征的复杂流动。使用由CALMET输出和PI-SWERL时空变量发射驱动的，计算有效的矢量化拉格朗日随机粒子扩散模型进行了粉尘扩散模拟。色散模型基于Langevin公式，并包括在惯性子范围内的湍流扩散和（数百万个粒子的）随机粒子运动，并假设粒子为离散单元而忽略了沉积。该模型根据PI-SWERL随时间变化的排放量估算值来估算初始粒子释放后粒子的扩散。然后在两个独立的顺风位置测试了结果，流动条件（R-2 = 0.89）和相似的受体PM10浓度（R-2 = 0.85）呈正相关。在平均流量条件下以及尘埃升高事件期间对这些观测值的评估表明，该模型框架可以捕获平均每日和每天PM10变异性的时空特征。在这项研究中，我们描述了模型框架的详细信息及其性能，以及其实现方式，以找到对受体部位影响最大的粉尘源，并评估在ODSVRA上采用的不同减尘策略以减轻PM10的影响在顺风接收器处。

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